Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia: testing existing methods and development and validation of a novel weighted score

Sarah Blackstock, Miles D. Witham, Alisha N. Wade, Amelia Crampin, David Beran, Graham D. Ogle, Justine I. Davies (Lead / Corresponding author)

    Research output: Contribution to journalArticle

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    Abstract

    Objectives: Verbal autopsy (VA) is a useful tool to ascertain cause of death where no other mechanisms exist. We aimed to assess the utility of VA data to ascertain deaths due to uncontrolled hyperglycaemia and to develop a weighted score (WS) to specifically identify cases. Cases were identified by a study or site physician with training in diabetes. These diagnoses were also compared with diagnoses produced by a standard computer algorithm (InterVA-4).

    Setting: This study was done using VA data from the Health and Demographic Survey sites in Agincourt in rural South Africa. Validation of the WS was done using VA data from Karonga in Malawi.

    Participants: All deaths from ages 1 to 49 years between 1992 and 2015 and between 2002 and 2016 from Agincourt and Karonga, respectively. There were 8699 relevant deaths in Agincourt and 1663 in Karonga.

    Results: Of the Agincourt deaths, there were 77 study physician classified cases and 58 computer algorithm classified cases. Agreement between study physician classified cases and computer algorithm classified cases was poor (Cohen's kappa 0.14). Our WS produced a receiver operator curve with area under the curve of 0.952 (95% CI 0.920 to 0.985). However, positive predictive value (PPV) was below 50% when the WS was applied to the development set and the score was dominated by the necessity for a premortem diagnosis of diabetes. Independent validation showed the WS performed reasonably against site physician classified cases with sensitivity of 86%, specificity of 99%, PPV of 60% and negative predictive value of 99%.

    Conclusion: Our results suggest that widely used VA methodologies may be missing deaths due to uncontrolled hyperglycaemia. Our WS may offer improved ability to detect deaths due to uncontrolled hyperglycaemia in large populations studies where no other means exist.

    Original languageEnglish
    Article numbere026331
    Pages (from-to)1-8
    Number of pages8
    JournalBMJ Open
    Volume9
    Issue number10
    Early online date18 Oct 2019
    DOIs
    Publication statusPublished - 18 Oct 2019

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    Hyperglycemia
    Autopsy
    Physicians
    Malawi
    South Africa
    Area Under Curve
    Cause of Death
    Demography
    Sensitivity and Specificity
    Population

    Keywords

    • diabetes & endocrinology
    • epidemiology
    • health informatics

    Cite this

    Blackstock, Sarah ; Witham, Miles D. ; Wade, Alisha N. ; Crampin, Amelia ; Beran, David ; Ogle, Graham D. ; Davies, Justine I. / Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia : testing existing methods and development and validation of a novel weighted score. In: BMJ Open. 2019 ; Vol. 9, No. 10. pp. 1-8.
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    abstract = "Objectives: Verbal autopsy (VA) is a useful tool to ascertain cause of death where no other mechanisms exist. We aimed to assess the utility of VA data to ascertain deaths due to uncontrolled hyperglycaemia and to develop a weighted score (WS) to specifically identify cases. Cases were identified by a study or site physician with training in diabetes. These diagnoses were also compared with diagnoses produced by a standard computer algorithm (InterVA-4).Setting: This study was done using VA data from the Health and Demographic Survey sites in Agincourt in rural South Africa. Validation of the WS was done using VA data from Karonga in Malawi.Participants: All deaths from ages 1 to 49 years between 1992 and 2015 and between 2002 and 2016 from Agincourt and Karonga, respectively. There were 8699 relevant deaths in Agincourt and 1663 in Karonga.Results: Of the Agincourt deaths, there were 77 study physician classified cases and 58 computer algorithm classified cases. Agreement between study physician classified cases and computer algorithm classified cases was poor (Cohen's kappa 0.14). Our WS produced a receiver operator curve with area under the curve of 0.952 (95{\%} CI 0.920 to 0.985). However, positive predictive value (PPV) was below 50{\%} when the WS was applied to the development set and the score was dominated by the necessity for a premortem diagnosis of diabetes. Independent validation showed the WS performed reasonably against site physician classified cases with sensitivity of 86{\%}, specificity of 99{\%}, PPV of 60{\%} and negative predictive value of 99{\%}.Conclusion: Our results suggest that widely used VA methodologies may be missing deaths due to uncontrolled hyperglycaemia. Our WS may offer improved ability to detect deaths due to uncontrolled hyperglycaemia in large populations studies where no other means exist.",
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    Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia : testing existing methods and development and validation of a novel weighted score. / Blackstock, Sarah; Witham, Miles D.; Wade, Alisha N.; Crampin, Amelia; Beran, David; Ogle, Graham D.; Davies, Justine I. (Lead / Corresponding author).

    In: BMJ Open, Vol. 9, No. 10, e026331, 18.10.2019, p. 1-8.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia

    T2 - testing existing methods and development and validation of a novel weighted score

    AU - Blackstock, Sarah

    AU - Witham, Miles D.

    AU - Wade, Alisha N.

    AU - Crampin, Amelia

    AU - Beran, David

    AU - Ogle, Graham D.

    AU - Davies, Justine I.

    N1 - ANW is supported by the Fogarty International Center of the National Institutes of Health under Award Number K43TW010698.

    PY - 2019/10/18

    Y1 - 2019/10/18

    N2 - Objectives: Verbal autopsy (VA) is a useful tool to ascertain cause of death where no other mechanisms exist. We aimed to assess the utility of VA data to ascertain deaths due to uncontrolled hyperglycaemia and to develop a weighted score (WS) to specifically identify cases. Cases were identified by a study or site physician with training in diabetes. These diagnoses were also compared with diagnoses produced by a standard computer algorithm (InterVA-4).Setting: This study was done using VA data from the Health and Demographic Survey sites in Agincourt in rural South Africa. Validation of the WS was done using VA data from Karonga in Malawi.Participants: All deaths from ages 1 to 49 years between 1992 and 2015 and between 2002 and 2016 from Agincourt and Karonga, respectively. There were 8699 relevant deaths in Agincourt and 1663 in Karonga.Results: Of the Agincourt deaths, there were 77 study physician classified cases and 58 computer algorithm classified cases. Agreement between study physician classified cases and computer algorithm classified cases was poor (Cohen's kappa 0.14). Our WS produced a receiver operator curve with area under the curve of 0.952 (95% CI 0.920 to 0.985). However, positive predictive value (PPV) was below 50% when the WS was applied to the development set and the score was dominated by the necessity for a premortem diagnosis of diabetes. Independent validation showed the WS performed reasonably against site physician classified cases with sensitivity of 86%, specificity of 99%, PPV of 60% and negative predictive value of 99%.Conclusion: Our results suggest that widely used VA methodologies may be missing deaths due to uncontrolled hyperglycaemia. Our WS may offer improved ability to detect deaths due to uncontrolled hyperglycaemia in large populations studies where no other means exist.

    AB - Objectives: Verbal autopsy (VA) is a useful tool to ascertain cause of death where no other mechanisms exist. We aimed to assess the utility of VA data to ascertain deaths due to uncontrolled hyperglycaemia and to develop a weighted score (WS) to specifically identify cases. Cases were identified by a study or site physician with training in diabetes. These diagnoses were also compared with diagnoses produced by a standard computer algorithm (InterVA-4).Setting: This study was done using VA data from the Health and Demographic Survey sites in Agincourt in rural South Africa. Validation of the WS was done using VA data from Karonga in Malawi.Participants: All deaths from ages 1 to 49 years between 1992 and 2015 and between 2002 and 2016 from Agincourt and Karonga, respectively. There were 8699 relevant deaths in Agincourt and 1663 in Karonga.Results: Of the Agincourt deaths, there were 77 study physician classified cases and 58 computer algorithm classified cases. Agreement between study physician classified cases and computer algorithm classified cases was poor (Cohen's kappa 0.14). Our WS produced a receiver operator curve with area under the curve of 0.952 (95% CI 0.920 to 0.985). However, positive predictive value (PPV) was below 50% when the WS was applied to the development set and the score was dominated by the necessity for a premortem diagnosis of diabetes. Independent validation showed the WS performed reasonably against site physician classified cases with sensitivity of 86%, specificity of 99%, PPV of 60% and negative predictive value of 99%.Conclusion: Our results suggest that widely used VA methodologies may be missing deaths due to uncontrolled hyperglycaemia. Our WS may offer improved ability to detect deaths due to uncontrolled hyperglycaemia in large populations studies where no other means exist.

    KW - diabetes & endocrinology

    KW - epidemiology

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